Presentation	1998/3/20 Chaotic Episodic Associative Memory Junya KITADA, Yuko OSANA, Masafumi HAGIWARA,
PDF Download Page	PDF download Page Link
Abstract(in Japanese)	(See Japanese page)
Abstract(in English)	In this paper, we propose Chaotic Episodic Associative Memory (CEAM). It can deal with complex episodes which have common terms. Temporal Associative Memory (TAM) and Episodic Associative Memory (EAM) have been proposed as models for episodic memory. However these models cannot deal with association of plural episodes that have common terms because the stored common patterns cause superimposed patterns. The proposed CEAM is based on the conventional TAM and has connections in the input layer for autoassociation. It also employs chaotic neurons in a part of the input layer. Each scene of the episodes is memorized together with its own contextual information. That is, the training set including common terms is converted into a form which doesn't include any common terms. The chaotic neurons in the input layer corresponding to contextual information change their states by chaos. As a result, the contextual information changes dynamically, which enables CEAM to recall plural episodes that have common terms. A series of computer simulations shows the effectiveness of the proposed model.
Keyword(in Japanese)	(See Japanese page)
Keyword(in English)	Episodic Memory / Associative Memory / Chaotic Neural Network
Paper #
Date of Issue

Conference Information
Committee	NC
Conference Date	1998/3/20(1days)
Place (in Japanese)	(See Japanese page)
Place (in English)
Topics (in Japanese)	(See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To	Neurocomputing (NC)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Chaotic Episodic Associative Memory
Sub Title (in English)
Keyword(1)	Episodic Memory
Keyword(2)	Associative Memory
Keyword(3)	Chaotic Neural Network
1st Author's Name	Junya KITADA
1st Author's Affiliation	Department of Electrical Engineering, Faculty of Science and Technology, Keio University()
2nd Author's Name	Yuko OSANA
2nd Author's Affiliation	Department of Electrical Engineering, Faculty of Science and Technology, Keio University
3rd Author's Name	Masafumi HAGIWARA
3rd Author's Affiliation	Department of Electrical Engineering, Faculty of Science and Technology, Keio University
Date	1998/3/20
Paper #
Volume (vol)	vol.97
Number (no)	624
Page	pp.pp.-
#Pages	8
Date of Issue